During my recent conversation with Aaron Levie, the CEO of Box, or the company’s “chief magician,” as his title used to read, he presented specific advice for CIOs during this period of digital transformation in change.

You can catch part one of our conversation and watch the entire video, which was episode 278 of the CXOTalk series of conversations with the world’s top innovators. View the video excerpt above and read Aaron’s edited comments below for insightful thoughts directed toward chief information officers.

The bottom line: Being adaptable is the key to maintaining CIO relevance to the business.

Connect between the new IT stack, culture, the role of the CIO, and where CIOs fit into this world?

We need to think about how do we take this set of technologies — again whether it’s Slack, Facebook Workplace, or Box — and how do you marry that with the cultural change that that organization is trying to drive? Often, it will come from a few discrete or distinct business initiatives.

Sometimes that might be that a company is trying. Let’s say it’s a retail operation and that company is trying to communicate with all of their retail environments. They want to be able to make sure everybody is aligned with maybe its new promotions, new policies, or new cultural efforts. Something like Facebook Workplace then, all of a sudden, becomes maybe the tool to go use to make sure that company can disseminate information.

We often get brought in when a company is facing the need to do much more internal and external collaboration. Maybe your partner ecosystem is changing. Maybe you have new partner relationships that you’re trying to drive. What you want to do is make sure that there is way less latency between sharing internally and externally. Box will get brought in to be able to help with that.

I think the CIO has to be highly tuned into: how the culture needs to change; and what are the business initiatives that relate to that cultural change? I think that often what gets missed when you go look at Silicon Valley, for instance, and you say, “Oh, we want to be like Google.” It’s important to think about which parts of Google are you trying to be like. Well, it’s not the Ping-Pong tables that make Google Google. It’s not the volleyball. It’s not the high-end chefs that make Google Google. Those are amenities — because they have this amazing business model.

The things that at least once made it Google were:

Twenty-percent time: Letting people go out and spend extra time building innovations that would not have normally come from the standard product roadmap.

A high-degree of autonomy: Where, if you had a great idea, you could go and present it to somebody.

A massive degree of information sharing: Google is notorious for being quite public internally with how the business is doing, how it can do better, etc. It has weekly Q&A sessions with the founders.

Those are the things that made Google Google. The volleyball is sort of a superficial façade on top of all that. I think we sometimes miss that. The only reason that you would want to wear sneakers or jeans to work or have open environments is merely because, when you create a more casual environment, it lets people’s guard down, so they can be more creative, and they can share ideas with one another better. It’s not that the jeans are the thing producing the innovation.

We have to think about the system that all of these components tie into. You’ll see the CEO, who thinks that they’re getting really cool because they’re now being more informal, but it’s not that interesting, because if the system itself is not using that informality to drive more creativity, then you didn’t accomplish anything from learning that lesson.

I think what we have to do is think about what is it about our business are we trying to change. Why are we trying to change it? Then, look to what are the underlying root sort of system-level things that drive that change that we’re trying to accomplish. Maybe it’s getting closer to our customer. Maybe it’s being able to hire a new type of talent in the organization. Maybe we think that we are getting slow at breakthrough innovation, so we want people to be more creative.

Maybe some organizations don’t have to change at all in this dimension because that’s just not a challenge. They want to get better logistics. I think it’s really important to understand: Where is innovation, where does this culture of innovation relate to your business model, and how do you design a work environment? How do you design a way of working that will facilitate whatever that business outcome is that you’re trying to drive?

You never used the term “digital transformation.” Is there a reason for that?

No. I felt like it was a long enough explanation without it.

I didn’t want to add more words. I think everything that I did discuss is obviously what I think people are trying to do when they talk about digital transformation. I think the challenge is digital transformation often sort of leads people to going straight to, “OK, I need this modern mobile app. I need Uber or Airbnb for my business.” That is often the necessary result of digital transformation, but the way of getting there is not that you just build an app, or you create an Airbnb for your business, it’s thinking through what is it about digital companies that allow digital innovation to occur so effectively.

It tends to be the case that a digital company, and in this case, I’m just going to think of the Airbnb of the world or the Spotify of the world, a digital company is run, usually. This is obviously stereotyping to some degree. It’s usually run in a more flat way — with more knowledge sharing, with faster moving, smaller units that can work in their own specific domain. That is usually the thing that enables a digital company to be successful, because often it comes from, in many senses, the way that we build software, which is small teams building projects.

That kind of ripples through the culture — where it’s almost hard to separate the GitHub mentality of software development, which is everything is out there right there. I can see every single change that ever happened, from the kind of culture that a software organization would expect, which is, I want to see everything. I want to have access to all of the information so that I can make the best decision, or I can look through the history of how we got to that decision.

These cultures are inseparable: The software culture, the digital development culture from how the rest of the company have to operate, the speed at which we have to operate. That is, I think, why you can’t accomplish digital transformation without tying into: How is the workplace going to function; how is the business model going to change; how are our underlying business processes going to relate to that transformation? We spend a lot of time thinking through those components.

How should CIOs think about investment in new technology versus existing technology?

Yeah, I mean I think it’s really interesting, because I would say, three years ago, we didn’t have to think through the data question as much around your architecture.

What’s sort of fundamental to AI is now you have to understand what data do you think is going to be important to driving your business in the future. Because that data will probably be improved by machine learning or, depending on the type of data, some form of artificial intelligence.

If you have an architecture design that doesn’t let you apply machine learning to that data, or you’re not using vendors that are very, very focused on making sure that you can apply machine learning or AI to that data, then you’re making decisions today that will create severe technology debt five years from now or 10 years from now.

Really understanding the architecture of how can you work with that information, and how do you work with that underlying data, and making sure it’s set up in such a way that eventually AI will be able to be applied to it. That’ll be different for different companies. If you’re an industrial company, then you probably want to think about how IoT data can be used against machine learning to improve customers’ maybe health checking of their infrastructure? That is going to have a particular set of decisions that you’re going to want to make about your architecture.

If you’re in the retail business, then you want to be thoughtful about, “OK, where is all this commerce data going? Where is data about my customers going?” You might want to make sure that it’s not going to become a black hole for you to be able to work against.

Being able to think through where, in my business, machine learning or AI will have the most impact, and make sure that you have an IT architecture that doesn’t preclude you from being able to apply AI or machine learning to whatever form of data, or whatever form of business process, is going to be most relevant to this kind of automation.

That’s the first thing — making sure that you’re designing a future-proof architecture. I don’t hear this a lot, but maybe we’ll put it into the design case more. I don’t hear the word “future-proof” enough.

I think that a lot of the ways that we design — for instance, RFPs — the way that we do IT decisions is very, very rear-view mirror oriented. It is what has this technology delivered thus far, and that is sort of what the RFP usually delivers. I think, instead, we need an RFP design and a mindset that is much more about what will this technology deliver in the future and not in the next six months or 12 months — not the near-term roadmap that you can see. Fundamentally, what will this technology be able to do in five years or 10 years?

For that, you’re not looking at the code or the features that have currently been developed. You’re looking for the principles of the company that you’re working with. You’re looking at where they sit in the value chain of the ecosystem. Are they going to be a vendor that is a neutral platform, or are they going to build out all of the technology themselves? How do they value openness versus closed systems? You want to understand the philosophy of the organizations that you’re working with just as much as you want to understand the current technology that they’ve written.

I don’t hear this enough from IT organizations. I think it’s a big miss, because I see a lot of IT organizations that will make short-term decisions that almost immediately become debt that they’re now baking into their IT architecture because they’ve gone with a vendor that maybe today could meet today’s RFP, but where the trajectory of that innovation is going to naturally asymptote, because, fundamentally, either the values of that organization or the architecture of that technology is built on has an obvious asymptote.

One example, to make this as real as possible: We, four or five years ago, would see a lot of customers say, “You know I really want to be able to share and collaborate on files, but I have to leverage my existing storage technology because I’ve already made an investment there. And so, I’m only going to implement software that works with my existing storage technology.”

What we would tell customers is, “If you do that, you have to recognize that the software that you’re implementing is frozen at today’s innovation.” This is a period right now in particular where there’s constant change in the cloud. There’s security change. There’s compliance change. There’s privacy change. There’s machine-learning change. You might be thinking you’re getting a good value because you’re going to leverage your existing storage technology, but, in fact, you’re freezing the amount of innovation you’re going to get at the moment you make this decision versus going with a platform where, every week, there’s innovation.

Obviously, I’m referring to us, but this could be true of any category of technology. Being able to think through where are the curves going and where do we see the innovation heading.

CXOTalkoffers in-depth conversations with the world’s top innovators. Be sure to watch our many episodes! Thumbnail image Creative Commons fromPixabay.

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Well-known expert on why IT projects fail, CEO of Asuret, a Brookline, MA consultancy that uses specialized tools to measure and detect potential vulnerabilities in projects, programs, and initiatives. Also a popular and prolific blogger, writing the IT Project Failures blog for ZDNet.